






from __future__ import annotations

import numpy as np






def    __magic_name__    (	SCREAMING_SNAKE_CASE				)     ->    tuple[np.ndarray, np.ndarray]:
							_lowercase							,							_lowercase							:   List[str] 							=   np.shape(SCREAMING_SNAKE_CASE				)
							if rows != columns:
														_lowercase							:   int 							=   (
														    '\'table\' has to be of square shaped array but got a '
														    F"""{rows}x{columns} array:\n{table}"""
														)
														raise ValueError(SCREAMING_SNAKE_CASE				)

							_lowercase							:   Optional[Any] 							=   np.zeros((rows, columns)				)
							_lowercase							:   Optional[Any] 							=   np.zeros((rows, columns)				)
							for i in range(SCREAMING_SNAKE_CASE				):
														for j in range(SCREAMING_SNAKE_CASE				):
																					_lowercase							:   Optional[Any] 							=   sum(lower[i][k] * upper[k][j] for k in range(SCREAMING_SNAKE_CASE				)				)
																					if upper[j][j] == 0:
																												raise ArithmeticError('No LU decomposition exists'				)
																					_lowercase							:   Dict 							=   (table[i][j] - total) / upper[j][j]
														_lowercase							:   Union[str, Any] 							=   1
														for j in range(SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE				):
																					_lowercase							:   Any 							=   sum(lower[i][k] * upper[k][j] for k in range(SCREAMING_SNAKE_CASE				)				)
																					_lowercase							:   Tuple 							=   table[i][j] - total
							return lower, upper


if __name__ == "__main__":
							import doctest

							doctest.testmod()








"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase_							=							logging.get_logger(__name__)

lowercase_							=							{
    'google/mobilenet_v2_1.4_224': 'https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json',
    'google/mobilenet_v2_1.0_224': 'https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json',
    'google/mobilenet_v2_0.75_160': 'https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json',
    'google/mobilenet_v2_0.35_96': 'https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}







class    __a						( __snake_case							):
				lowerCamelCase     :       List[Any]			       ='mobilenet_v2'







				def __init__( self      ,	UpperCAmelCase=3      ,	UpperCAmelCase=224      ,	UpperCAmelCase=1.0      ,	UpperCAmelCase=8      ,	UpperCAmelCase=8      ,	UpperCAmelCase=6      ,	UpperCAmelCase=32      ,	UpperCAmelCase=True      ,	UpperCAmelCase=True      ,	UpperCAmelCase="relu6"      ,	UpperCAmelCase=True      ,	UpperCAmelCase=0.8      ,	UpperCAmelCase=0.0_2      ,	UpperCAmelCase=0.0_0_1      ,	UpperCAmelCase=255      ,	**UpperCAmelCase      ,	):

					'''simple docstring'''






					super().__init__(**UpperCAmelCase   )

					if depth_multiplier <= 0:
						raise ValueError('''depth_multiplier must be greater than zero.'''   )

					lowerCAmelCase_      							=			num_channels
					lowerCAmelCase_      							=			image_size
					lowerCAmelCase_      							=			depth_multiplier
					lowerCAmelCase_      							=			depth_divisible_by
					lowerCAmelCase_      							=			min_depth
					lowerCAmelCase_      							=			expand_ratio
					lowerCAmelCase_      							=			output_stride
					lowerCAmelCase_      							=			first_layer_is_expansion
					lowerCAmelCase_      							=			finegrained_output
					lowerCAmelCase_      							=			hidden_act
					lowerCAmelCase_      							=			tf_padding
					lowerCAmelCase_      							=			classifier_dropout_prob
					lowerCAmelCase_      							=			initializer_range
					lowerCAmelCase_      							=			layer_norm_eps
					lowerCAmelCase_      							=			semantic_loss_ignore_index







class    __a						( __snake_case							):
				lowerCamelCase     :       Optional[int]			       =version.parse('1.11'							)







				@property
				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					return OrderedDict([('''pixel_values''', {0: '''batch'''})]   )







				@property
				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					if self.task == "image-classification":
						return OrderedDict([('''logits''', {0: '''batch'''})]   )
					else:
						return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]   )







				@property
				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					return 1E-4